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Proceedings Paper

Computer vision hardware system for automating rough mills of furniture plants
Author(s): Richard W. Conners; Chong T. Ng; Thomas H. Drayer; Joseph G. Tront; D. Earl Kline; Charley J. Gatchell
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Paper Abstract

The rough mill of a hardwood furniture or fixture plant is the place where dried lumber is cut into the rough parts that will be used in the rest of the manufacturing process. Approximately a third of the cost of operating the rough mill is the cost of the raw material. Hence any increase in the number of rough parts produced from a given volume of raw material can markedly affect profit margins of a company. To automate this initial cutup requires a computer vision system that can locate and identify surface defects on boards. This paper describes continuing research aimed at developing such a vision system. An important part of this research activity is the design effort going into creating a prototype hardware system, a system that will be able to scan variable width, variable length hardwood boards at industrial speeds of two to three linear feet per second. This system is being designed to handle full length boards up to sixteen feet long. The components of the prototype are a materials handling system, an imaging system, a image processing hardware system, and a software system for performing the necessary recognition tasks and for performing all the necessary control functions. The design of each of these components will be described with the emphasis placed on hardware development.

Paper Details

Date Published: 1 January 1990
PDF: 12 pages
Proc. SPIE 1293, Applications of Artificial Intelligence VIII, (1 January 1990); doi: 10.1117/12.21127
Show Author Affiliations
Richard W. Conners, Virginia Polytechnic Institute and State Univ. (United States)
Chong T. Ng, Virginia Polytechnic Institute and State Univ. (United States)
Thomas H. Drayer, Virginia Polytechnic Institute and State Univ. (United States)
Joseph G. Tront, Virginia Polytechnic Institute and State Univ. (United States)
D. Earl Kline, Virginia Polytechnic Institute and State Univ. (United States)
Charley J. Gatchell, Northeastern Forest Experiment Station (United States)

Published in SPIE Proceedings Vol. 1293:
Applications of Artificial Intelligence VIII
Mohan M. Trivedi, Editor(s)

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